具有分数拉普拉奇和随时间变化系数的后向扩散方程的索波列夫型正则化方法

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS ACS Applied Bio Materials Pub Date : 2024-08-28 DOI:10.1002/mma.10425
Tran Thi Khieu, Tra Quoc Khanh
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引用次数: 0

摘要

本研究涉及一个难题,即在多维空间中重建具有分数拉普拉斯和随时间变化系数的后向扩散方程的历史分布。所研究的问题是通过索波列方程方法正则化的。与以往的研究不同,为了证明正则化解向精确解的收敛性,我们只需要一个非常微弱和自然的先验条件,即解属于标准的 Lebesgue 空间。这可以通过适当运用 Lebesgue 主导收敛定理来实现。如果我们进一步施加更强的先验条件,就可以知道收敛速度有多快。最后,我们提供了一些基于 MATLAB 的数值示例,以证实所提方法的效率。
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Sobolev‐type regularization method for the backward diffusion equation with fractional Laplacian and time‐dependent coefficient
This work is concerned with an ill‐posed problem of reconstructing the historical distribution of a backward diffusion equation with fractional Laplacian and time‐dependent coefficient in multidimensional space. The investigated problem is regularized by a Sobolev‐type equation method. Unlike previous works, to prove the convergence of the regularized solution to the exact one, we only require a very weak and natural a priori condition that the solution belongs to the standard Lebesgue space . This is done by suitably employing the Lebesgue‐dominated convergence theorem. If we go further to impose a stronger a priori condition, one may know how fast the convergence is. Finally, some MATLAB‐based numerical examples are provided to confirm the efficiency of the proposed method.
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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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